Application of ontologies and digital libraries in school education

The article discusses the application of digital libraries, including a network of ontologies and structured databases, in the education of students in secondary schools. The multi-agent platform of VES (the Virtual Educational Space) is presented, based on the reference architecture of ViPS (the Virtual Physical Space), which is being developed in the DeLC (the Distributed e-Learning Center) laboratory of the University of Plovdiv “Paisii Hilendarski”. The information and data in VES are supported by a hybrid structure of ontologies and databases, as the designed services are supported by intelligent agents and personal assistants. Through the interaction between these intelligent components, some functionalities are modeled such as conducting virtual excursions in the teaching of various school subjects, automatic generation of tests and surveys, development of project tasks, game-based training, etc.

AN APPROACH TO THE APPLICATION OF ONTOLOGIES AND DIGITAL LIBRARIES IN SCHOOL EDUCATION

The article presents an approach for the application of digital libraries, including a network of ontologies and structured databases in the education of school students in literature, history, geography and biology. The general architecture of a multi-agent platform based on the reference framework of the ViPS (Virtual Physical Space) system, which is being developed in the DeLC Laboratory of the Plovdiv University Paisii Hilendarski“, will be considered. The information and data in this platform are maintained by a hybrid structure of ontologies and databases, with the designed services maintained by intelligent agents and personal assistants. Through interaction between these intelligent components, functionalities are modelled, such as: conducting virtual tours in the teaching of different subjects; automatic generation of questionnaires, tests and surveys; development of project assignments; game-based learning; group assignments, etc. These functionalities and services are aimed at classroom training as well as interest clubs.

Intelligent decision support in logistics systems

В статье изложен подход, обеспечивающий реализацию комплексных логистических технологий на основе координации перевозок и процедур обработки грузов в интересах выполнения стратегии доставки «точно в срок» и «от двери до двери». Важнейшим фактором, обеспечивающим достижение высокого уровня качества управления транспортно-технологическими процессами, является формирование и использование релевантной системы интеллектуальной поддержки принятия решений, сформированной с учетом достижений новых информационных технологий. Представлены основные классы задач, решаемые при управлении логистическими системами. Отмечено, что система интеллектуальной поддержки принятия решений позволяет осуществлять планирование, управление и контроль всего логистического процесса в режиме реального времени с учетом требования минимизации используемых различного рода ресурсов. Ключевым элементом указанной системы является база знаний, содержащая формализованные знания предметной области. Дано представление мультиагентной платформы системы интеллектуальной поддержки принятия решений, показано ее использование при выборе комплексных логистических технологий. Для иллюстрации подхода была рассмотрена конкретная функциональная задача по принятию решения о выборе вида транспорта исходя из требуемых сроков доставки продукции. Отмечены преимущества системы интеллектуальной поддержки в выборе эффективных комплексных логистических технологий. The article outlines an approach that ensures the implementation of complex logistics technologies based on the coordination of transportation and cargo handling procedures in order to fulfill the delivery strategy "just in time" and "door to door". The most important factor ensuring the achievement of a high level of quality management of transport and technological processes is the formation and use of a relevant system of intelligent decision support, formed taking into account the achievements of new information technologies. The main classes of problems solved in the management of logistics systems are presented. It is noted that the system of intelligent decision-making support allows planning, management and control of the entire logistics process in real time, taking into account the requirement to minimize the various kinds of resources used. The main element of this system is the knowledge base containing formalized knowledge of the subject area. The multi-agent platform of the intelligent decision support system is presented; its use is shown when choosing complex logistics technologies. To illustrate the approach, a specific functional task for making a decision on the choice of a mode of transport based on the required delivery time of products was considered. The advantages of the system of intellectual support in the selection of effective complex logistics technologies were noted.

Multi Agent System Based Approach for Industrial Process Simulation

Industrial systems become more and more complex. This complexity is due to the great number of elements that compose them and their interactions. This paper describes a multi-agent approach for modeling such systems. All of their parts are considered and are modeled by using adequate agents. The set of preoccupations were identified to find convenient multi agent models for their resolutions. Then, we implemented our application by using a MADKIT multi-agent platform. The main goal of this work is to build a simulator based on reactive agents able to translate this complex industrial system into a data processing programs that can represent its structure, its behavior, its interaction, its control loops and verify the integrity and its proper functioning. A concrete application of this approach was materialized by building an industrial gas process simulator.Industrial systems become more and more complex. This complexity is due to the great number of elements that compose them and their interactions. This paper describes a multi-agent approach for modeling such systems. All of their parts are considered and are modeled by using adequate agents. The set of preoccupations were identified to find convenient multi agent models for their resolutions. Then, we implemented our application by using a MADKIT multi-agent platform. The main goal of this work is to build a simulator based on reactive agents able to translate this complex industrial system into a data processing programs that can represent its structure, its behavior, its interaction, its control loops and verify the integrity and its proper functioning. A concrete application of this approach was materialized by building an industrial gas process simulator.Industrial systems become more and more complex. This complexity is due to the great number of elements that compose them and their interactions. This paper describes a multi-agent approach for modeling such systems. All of their parts are considered and are modeled by using adequate agents. The set of preoccupations were identified to find convenient multi agent models for their resolutions. Then, we implemented our application by using a MADKIT multi-agent platform. The main goal of this work is to build a simulator based on reactive agents able to translate this complex industrial system into a data processing programs that can represent its structure, its behavior, its interaction, its control loops and verify the integrity and its proper functioning. A concrete application of this approach was materialized by building an industrial gas process simulator.Industrial systems become more and more complex. This complexity is due to the great number of elements that compose them and their interactions. This paper describes a multi-agent approach for modeling such systems. All of their parts are considered and are modeled by using adequate agents. The set of preoccupations were identified to find convenient multi agent models for their resolutions. Then, we implemented our application by using a MADKIT multi-agent platform. The main goal of this work is to build a simulator based on reactive agents able to translate this complex industrial system into a data processing programs that can represent its structure, its behavior, its interaction, its control loops and verify the integrity and its proper functioning. A concrete application of this approach was materialized by building an industrial gas process simulator.

The Student Relationship Management System Process with Intelligent Conversational Agent Platform

The objectives of the study were as follows: (1) to study the student relationship management system process with intelligent conversational agent platform, (2) to design the student relationship management system process with intelligent conversational agent platform, and (3) to evaluate the student relationship management system process with intelligent conversational agent platform provided by seven experts who had experience in a related field. The study findings suggested that the student relationship management system process with intelligent conversational agent platform consists of four main dimensions: (1) Strategic, (2) Operational, (3) Analytical, and (4) Collaborative. After analyzing the data, it showed that the overall result of the evaluation of the student relationship management system process with intelligent conversational agent platform was at a very high appropriate level, which can be applied to real situations.

HADES: A Multi-Agent Platform to Reduce Congestion Anchoring Based on Temporal Coordination of Vessel Arrivals—Application to the Multi-Client Liquid Bulk Terminal in the Port of Cartagena (Spain)

Ports are key factors in international trade, and new port terminals are quite costly and time consuming to build. Therefore, it is necessary to optimize existing infrastructure to achieve sustainability in logistics. This problem is more complex in multi-client port terminals, where quay infrastructure is shared among terminal operators who often have conflicting interests. Moreover, the berth allocation problem in liquid bulk terminals implies demanding restrictions due to the reduced flexibility in berth allocation for these types of goods. In this context, this paper presents HADES, a multi-agent platform, and the experience of its pilot use in the Port of Cartagena. HADES is a software platform where agents involved in vessel arrivals share meaningful but limited information. This is done to alleviate potential congestion in multi-client liquid bulk terminals, promoting a consensus where overall congestion anchoring is reduced. A study is presented using a mixed integer linear program (MILP) optimization model to analyze the maximum theoretical reduction in congestion anchoring, depending on the flexibility of vessel arrival time changes. Results show that 6 h of flexibility is enough to reduce congestion anchoring by half, and 24 h reduces it to negligible values. This confirms the utility of HADES, which is also briefly described.

An Efficient Agent Based Data Management Method of NoSQL Environments for Health Care Applications

Background: As medical knowledge is continuously expanding and diversely located, Health Information Technology (HIT) applications are proposed as a good prospect for improving not only the efficiency and the effectiveness but also the quality of healthcare services delivery. The technologies expected to shape such innovative HIT architectures include: Mobile agents (Mas) and NoSQL technologies. Mobile agents provide an inherent way of tackling distributed problems of accessing heterogeneous and spatially diverse data sources. NoSQL technology gains ground for the development of scalable applications with non-static and open data schema from complex and diverse sources. Methods and Design: This paper conducts a twofold study: It attempts a literature review of the applications based on the mobile agent (MA) and NoSQL technologies for healthcare support services. Subsequently, a pilot system evaluates the NoSQL technology against the relational one within a distributed environment based on mobile agents for information retrieval. Its objective is to study the feasibility of developing systems that will employ ontological data representation and task implementation through mobile agents towards flexible and transparent health data monitoring. Results and Discussion: The articles studied focus on applying mobile agents for patient support and healthcare services provision thus as to make a positive contribution to the treatment of chronic diseases. In addition, attention is put on the design of platform neutral techniques for clinical data gathering and dissemination over NoSQL. The experimental environment was based on the Apache Jena Fuseki NoSQL server and the JAVA Agent DEvelopment Framework -JADE agent platform. The results reveal that the NoSQL implementation outperforms the standard relational one.